Exploiting Programmable Network Interfaces for Parallel Query Execution in Workstation Clusters

Workstation clusters equipped with high performance interconnect having programmable network processors facilitate interesting opportunities to enhance the performance of parallel application run on them. In this paper, we propose schemes where certain application level processing in parallel database query execution is performed on the network processor. We evaluate the performance of TPC-H queries executing on a high end cluster where all tuple processing is done on the host processor, using a timed Petri net model, and find that tuple processing costs on the host processor dominate the execution time. These results are validated using a small cluster. We therefore propose 4 schemes where certain tuple processing activity is offloaded to the network processor. The first 2 schemes offload the tuple splitting activity - computation to identify the node on which to process the tuples, resulting in an execution time speedup of 1.09 relative to the base scheme, but with I/O bus becoming the bottleneck resource. In the 3rd scheme in addition to offloading tuple processing activity, the disk and network interface are combined to avoid the I/O bus bottleneck, which results in speedups up to 1.16, but with high host processor utilization. Our 4th scheme where the network processor also performs apart of join operation along with the host processor, gives a speedup of 1.47 along with balanced system resource utilizations. Further we observe that the proposed schemes perform equally well even in a scaled architecture i.e., when the number of processors is increased from 2 to 64

Computational Analysis of Flow through a Multiple Nozzle Driven Laser Cavity and Diffuser

Computations have been carried out for simulating supersonic flow through a set of converging-diverging nozzles with their expanding jets forming a laser cavity and flow patterns through diffusers, past the cavity. A thorough numerical investigation with 3-D RANS code is carried out to capture the flow distribution which comprises of shock patterns and multiple supersonic jet interactions. The analysis of pressure recovery characteristics during the flow through the diffusers is an important parameter of the simulation and is critical for the performance of the laser device. The results of the computation have shown a close agreement with the experimentally measured parameters as well as other established results indicating that the flow analysis done is found to be satisfactory.

Performance Modeling based on Multidimensional Surface Learning for Performance Predictions of Parallel Applications in Non-Dedicated Environments

Modeling the performance behavior of parallel applications to predict the execution times of the applications for larger problem sizes and number of processors has been an active area of research for several years. The existing curve fitting strategies for performance modeling utilize data from experiments that are conducted under uniform loading conditions. Hence the accuracy of these models degrade when the load conditions on the machines and network change. In this paper, we analyze a curve fitting model that attempts to predict execution times for any load conditions that may exist on the systems during application execution. Based on the experiments conducted with the model for a parallel eigenvalue problem, we propose a multi-dimensional curve-fitting model based on rational polynomials for performance predictions of parallel applications in non-dedicated environments. We used the rational polynomial based model to predict execution times for 2 other parallel applications on systems with large load dynamics. In all the cases, the model gave good predictions of execution times with average percentage prediction errors of less than 20%

Coordination-driven self-assembly of 2D-metallamacrocycles using a shape-selective Pt(2)(II)-organometallic 90 degrees acceptor: design, synthesis and sensing study

Synthesis of a series of two-dimensional metallamacrocycles via coordination-driven self-assembly of a shape-selective Pt(2)(II)-molecular building unit incorporating carbazole-ethynyl functionality is described. An equimolar (1 : 1) combination of a Pt(2)(II)-organometallic 90 degrees acceptor, 1, with rigid linear ditopic donors (L(a) and L(b)) afforded [4 + 4] self-assembled octanuclear molecular squares, 2 and 3, in quantitative yields, respectively [L(a) = 4,4'-bipyridine; L(b) = trans-1,2-bis(4-pyridyl)ethylene]. Conversely, a similar treatment of 1 with an amide-based unsymmetrical flexible ditopic donor, L(c), resulted in the formation of a [2 + 2] self-sorted molecular rhomboid (4a) as a single product [L(c) = N-(4-pyridyl)isonicotinamide]. Despite the possibility of several linkage isomeric macrocycles (rhomboid, triangle and square) due to the different connectivity of L(c), the formation of a single and symmetrical molecular rhomboid (4a) as the only product is an interesting observation. All the self-assembled macrocycles (2, 3 and 4a) were fully characterized by multinuclear NMR ((1)H and (31)P) and ESI-MS analysis. Further structural insights about the size and shape of the macrocycles were obtained through energy minimization using density functional theory (DFT) calculations. Decoration of the starting carbazole building unit with Pt-ethynyl functionality enriches the assemblies to be more p-electron rich and luminescent in nature. Macrocycles 2 and 3 could sense the presence of electron deficient nitroaromatics in solution by quenching of the initial intensity upon gradual addition of picric acid (PA). They exhibited the largest quenching response with high selectivity for nitroaromatics compared to several other electron deficient aromatics tested.

Parallel Computation of 2D Morse-Smale Complexes

The Morse-Smale complex is a useful topological data structure for the analysis and visualization of scalar data. This paper describes an algorithm that processes all mesh elements of the domain in parallel to compute the Morse-Smale complex of large two-dimensional data sets at interactive speeds. We employ a reformulation of the Morse-Smale complex using Forman's Discrete Morse Theory and achieve scalability by computing the discrete gradient using local accesses only. We also introduce a novel approach to merge gradient paths that ensures accurate geometry of the computed complex. We demonstrate that our algorithm performs well on both multicore environments and on massively parallel architectures such as the GPU.

An operator-splitting finite element method for the efficient parallel solution of multidimensional population balance systems

A finite element method for solving multidimensional population balance systems is proposed where the balance of fluid velocity, temperature and solute partial density is considered as a two-dimensional system and the balance of particle size distribution as a three-dimensional one. The method is based on a dimensional splitting into physical space and internal property variables. In addition, the operator splitting allows to decouple the equations for temperature, solute partial density and particle size distribution. Further, a nodal point based parallel finite element algorithm for multi-dimensional population balance systems is presented. The method is applied to study a crystallization process assuming, for simplicity, a size independent growth rate and neglecting agglomeration and breakage of particles. Simulations for different wall temperatures are performed to show the effect of cooling on the crystal growth. Although the method is described in detail only for the case of d=2 space and s=1 internal property variables it has the potential to be extendable to d+s variables, d=2, 3 and s >= 1. (C) 2011 Elsevier Ltd. All rights reserved.

Simulation-driven design of helmets for head impact protection using an injury-based criterion

The current paper suggests a new procedure for designing helmets for head impact protection for users such as motorcycle riders. According to the approach followed here, a helmet is mounted on a featureless Hybrid 3 headform that is used in assessing vehicles for compliance to the FMVSS 201 regulation in the USA for upper interior head impact safety. The requirement adopted in the latter standard, i.e. not exceeding a threshold HIC(d) limit of 1000, is applied in the present study as a likely criterion for adjudging the efficacy of helmets. An impact velocity of 6 m/s (13.5 mph) for the helmet-headform system striking a rigid target can probably be acceptable for ascertaining a helmet's effectiveness as a countermeasure for minimizing the risk of severe head injury. The proposed procedure is demonstrated with the help of a validated LS-DYNA model of a featureless Hybrid 3 headform in conjunction with a helmet model comprising an outer polypropylene shell to the inner surface of which is bonded a protective polyurethane foam padding of a given thickness. Based on simulation results of impact on a rigid surface, it appears that a minimum foam padding thickness of 40 mm is necessary for obtaining an acceptable value of HIC(d).

Language identification using parallel sub-word recognition

Parallel sub-word recognition (PSWR) is a new model that has been proposed for language identification (LID) which does not need elaborate phonetic labeling of the speech data in a foreign language. The new approach performs a front-end tokenization in terms of sub-word units which are designed by automatic segmentation, segment clustering and segment HMM modeling. We develop PSWR based LID in a framework similar to the parallel phone recognition (PPR) approach in the literature. This includes a front-end tokenizer and a back-end language model, for each language to be identified. Considering various combinations of the statistical evaluation scores, it is found that PSWR can perform as well as PPR, even with broad acoustic sub-word tokenization, thus making it an efficient alternative to the PPR system.